Computing systems and associated networks have revolutionized the way human beings work, play, and communicate. Nearly every aspect of our lives is affected in some way by computing systems. The proliferation of networks has allowed computing systems to share data and communicate thereby vastly increasing information access. For this reason, the present age is often referred to as the “information age”.
One key technology that facilitates access to information is the database. A query is a formalized request to access information from the database. Often queries are issued against one or more or all tables of a database using a defined query language having defined query semantics (often referred to as a structured query). In order to allow more natural human access to such databases, natural language query technology has developed in which uses may use more natural language queries (at least compared to structured queries). The natural language queries are then subject to a natural language interpretation model (which may include one or both of syntactic and semantic models) to thereby formulate an estimate of a corresponding structured query.
The nuances of human language have made the problem of converting natural human language into computer-interpretive form a difficult problem to resolve, even for modern technology. Often, natural language interpretation models provide results that do not exactly match the intent of the user, causing the querier to modify the query results to reflect a more desired result. This might be because the natural language interpretation model simply does not understand the semantics and the syntax intended for the natural language query.
The subject matter claimed herein is not limited to embodiments that solve any disadvantages or that operate only in environments such as those described above. Rather, this background is only provided to illustrate one exemplary technology area where some embodiments described herein may be practiced.